the 2025 guide to intelligent document processing (IDP)
Give precious time back to your team, slash costs, and scale massively.
Document processing seems to evolve as fast as the latest smartphone—just when you think you’re up to date, a new upgrade is here.
Case in point: In the past few years, Generative AI (GenAI) has revolutionized Intelligent Document Processing (IDP), filling the gaps where existing solutions have fallen short. Indeed, GenAI is enhancing accuracy, speeding up processing, automating complex tasks, cutting costs, and boosting productivity like never before.
If your business handles a large volume of documents—such as medical records, claims, invoices, purchase orders, bank statements, or loan applications—then a GenAI-fueled IDP service is exactly what you need to make your operations smoother, more accurate, and less expensive.
Now is the time to embrace this technology.
Spend a few minutes learning about Intelligent Document Processing. Just like upgrading to the latest smartphone gives you faster performance and new capabilities, embracing modern IDP technology will transform your business operations. This guide, updated annually, will walk you through all things IDP: evolution, implementation, best practices, and what’s coming next. This knowledge will improve your document management operation and future-proof your business.
table of contents
what is intelligent document processing?
Intelligent Document Processing is an advanced technology that combines AI, machine learning (ML), optical character recognition (OCR), and automation to capture, extract, and process data from a wide variety of document formats.
Unlike traditional document processing, which relies heavily on manual input and predefined rules, IDP leverages AI to understand and manage both structured and unstructured data, improving efficiency and accuracy in document handling.
What is unstructured data?
Analysts estimate that 80% to 90% of all data is unstructured, meaning it doesn’t fit neatly into predefined formats or databases. Unstructured documents encompass a wide range of formats, including PDFs, scanned images, emails, contracts, invoices, and other text or visual content.
Forms and emails often contain unstructured data like customer inquiries, feedback, or order details, which are typically presented in a freeform manner without following a consistent template. This type of data is more challenging to process and analyze, making it essential for businesses to have the right tools and strategies in place to manage it effectively.
What is structured data?
Structured data is information organized clearly and consistently, making it easy to search, sort, and analyze. It’s typically stored in tables, spreadsheets, or databases, where each piece of data fits neatly into predefined categories, like rows and columns.
For example, a fixed form listing customer names, email addresses, and phone numbers in the same way repeatedly is considered structured data because each piece of information is stored in its own specific field. This organization makes it straightforward to understand, retrieve, and work with the data.
what is the current landscape of the IDP market?
Booming and transformative. The global IDP market is on a remarkable growth trajectory, projected to reach USD 7.38 billion by 2028, driven by a compound annual growth rate (CAGR) of approximately 40.94% from 2023 to 2028.
This rapid expansion is fueled by the integration of big data analytics and cloud-based solutions, which are enabling organizations to automate document processing and derive valuable insights from unstructured data. As companies seek to reduce document management costs and enhance efficiency, digital transformation initiatives are becoming essential.
Key trends shaping the IDP market:
- Crowded vendor landscape: With numerous players vying for market share, continued consolidation is likely as vendors seek to strengthen their positions and expand their capabilities.
- Integration of advanced AI: IDP vendors are incorporating GenAI and Large Language Models (LLMs) to enhance decision-making capabilities, streamline user interfaces, and extend the functionality of document processing across various types and use cases.
- Innovative solution delivery: Today’s customers demand IDP solutions that integrate seamlessly with their existing technology infrastructures and processes, allowing for smooth adoption and minimal disruption.
- Automation workflow integration: IDP is pivotal in automating document workflows. As automation becomes more widespread, the need for high accuracy and flexibility to handle diverse document types is crucial.
- Regulatory compliance: As privacy regulations like GDPR and CCPA evolve, IDP solutions must assist in managing Personally Identifiable Information (PII) and ensuring compliance through effective data capture, storage, and auditing processes.
a brief history of document processing technologies
Manual data entry (Pre-1960s to 1970s): Before computers, businesses relied heavily on manual data entry, where clerks and employees would manually input data into ledgers or early mechanical systems. This era lasted until computers became more accessible and began replacing manual processes.
Optical character recognition (OCR) (1970s to 1990s): The early development of OCR technology began in the 1970s, but it wasn’t widely adopted until the 1980s and 1990s. Early OCR systems could recognize and digitize printed text but were limited by font types, image quality, and layout variations.
Rule-based automation (1980s to 1990s): Next up was rule-based automation. Businesses began using software that could follow predefined rules to automate simple document processing tasks. However, these systems required constant updates and were limited in handling unstructured data.
AI and ML (2000s to Present): The integration of AI and ML into document processing solutions and services started gaining traction in the 2000s. By the 2010s, these technologies became more mainstream, enabling significant advancements in processing unstructured data. AI and ML allowed systems to learn from data, improving accuracy and flexibility.
Intelligent Document Processing (2010s to 2023): IDP represents the gold standard of document processing, combining AI, ML, OCR, and other technologies. IDP services became more prominent in the 2010s as businesses sought to automate complex document workflows and enhance operational efficiency. The adoption of IDP has accelerated in the 2020s, driven by digital transformation and the need to process large volumes of unstructured data.
what does the future hold for intelligent document processing?
First is the increasing integration of ML. As ML models evolve, they’ll enable systems to recognize and extract data from complex documents with greater accuracy and efficiency. Smart document solutions are also becoming more adaptive, allowing businesses to handle a broader range of document types and formats automatically.
AI is being used to predict and preemptively address issues before they arise, which makes document processing faster and more reliable. Data redaction is becoming essential, ensuring sensitive information is securely removed or obscured to meet privacy regulations like GDPR and protect against unauthorized access.
Another significant trend is the rise of cloud-based solutions, which offer businesses the scalability to expand their document processing capabilities seamlessly as they grow.
Meanwhile, GenAI is set to revolutionize IDP by going beyond simple data extraction. It can anticipate missing information, propose corrections, and even generate summaries or detailed reports, simulating human understanding to enhance both speed and accuracy.
These technological advancements will greatly benefit businesses by reducing manual tasks, lowering costs, and improving efficiency. Companies will be able to spend less time managing documents and more time on strategic initiatives. By leveraging these smart tools, businesses can gain valuable insights, ensure compliance, and maintain a competitive edge.
GenAI-powered intelligent document processing
AI is the 4th wave for IDP (2023 to Present): Unlike previous waves focused on rule-based systems and basic ML, this new era leverages GenAI and LLMs to transform how documents are understood and processed. GenAI-powered IDP is enhancing accuracy, speeding up workflows, and automating complex tasks with unprecedented precision.
By integrating advanced AI, IDP solutions can now handle diverse document types and unstructured data, making them indispensable for organizations seeking to boost productivity, reduce costs, and remain agile in today’s fast-changing digital world.
Pro tip:
For those who already have a legacy data capture solution in place, fear not. Look for a provider that can seamlessly integrate with existing tech and/or processes for a quick ROI.
See how that works by watching the following video:
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More Informationhow intelligent document processing works
To understand how IDP software works, it’s important to understand these 5 steps.
STEP 1: DOCUMENT PREPARATION
This initial step prepares documents by enhancing image quality, categorizing documents by type, and separating multi-page documents. Ensuring clear, organized, and correctly classified input lays the groundwork for accurate data capture and efficient processing.
STEP 2: INTELLIGENT DATA CAPTURE
Next is intelligent data capture, which uses technology to understand and capture information from documents. This means it can read and recognize text, numbers, and even handwriting in both digital and paper formats.
STEP 3: AUTOMATED DATA EXTRACTION
Once information is captured, automated data extraction kicks in. This step pulls out relevant data from the documents. It automatically picks up details like names, dates, or amounts without needing someone to do it manually.
STEP 4: AI AND ML
AI and ML help the system get smarter over time. As more documents are processed, the system learns to recognize patterns and improves its accuracy, making the whole process faster and more reliable.
STEP 5: HITL VALIDATION
Humans are necessary to ensure accuracy, particularly in complex or ambiguous cases. In this step, humans validate any extracted data with a low-confidence threshold, correct any errors, and provide feedback that helps the system improve. This combination of automated processing and human expertise ensures the highest levels of accuracy and reliability.
This video explains the critical role humans play in IDP solutions:
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More Informationwhat can intelligent document processing services do?
Data extraction
Intelligent Document Processing automates the extraction of data from complex and unstructured documents, a task that traditionally required significant manual effort. It uses advanced technologies like OCR, natural language processing (NLP), ML, and GenAI to process these documents.
OCR converts scanned images and handwritten text into machine-readable formats, but on its own, it can’t interpret the content’s meaning. This is where NLP comes in, allowing the system to understand the context of the text, much like a human would.
ML further enhances this by learning from patterns and improving accuracy over time, allowing the system to extract specific information like names, dates, and amounts from various document types accurately.
GenAI takes IDP to the next level by extracting and interpreting data and generating new, meaningful content based on the information. It enhances the system’s ability to handle diverse and complex document types by predicting and filling in missing data, refining document categorization, and even simulating human-like understanding. This allows IDP solutions to provide more accurate insights and automate decision-making processes that would typically require human judgment.
Document classification, separation, and categorization
IDP can automatically classify and categorize documents, and separate documents from one another. After OCR converts the document into a readable format, ML models classify the documents based on specific features like keywords, structure, or patterns. NLP helps by understanding the text’s context, further refining the classification process.
When a file contains multiple documents, the system can segment and categorize each one separately using computer vision techniques. This automated classification streamlines document management, reducing processing time and minimizing human error.
Data validation
IDP tools ensure the accuracy and reliability of extracted data through a robust validation process. After data is extracted, it’s checked for completeness and consistency.
Advanced algorithms cross-verify the data against predefined business rules, such as ensuring an invoice date is not in the future or that an order number follows a specific format.
The system can also compare extracted data with other documents or external sources for further data verification. If any data fails these checks, It’s flagged for manual review, ensuring that only accurate and reliable data moves forward in automated business processes.
Intelligence and insights
IDP solutions transform raw data into valuable insights by leveraging AI technologies like NLP and ML after data is extracted and validated. These tools analyze the information to uncover patterns, predict trends, and even assess sentiment in customer communications.
IDP visualizes data through graphs and charts, making it easier for decision-makers to understand and act on insights and integrates seamlessly with existing Business Intelligence tools. This integration provides high-quality data that enhances the accuracy of business reports and analytics, enabling more informed decisions.
are humans involved in intelligent document processing?
- Human-in-the-Loop (HITL): In many IDP systems, humans play a role in validating and correcting data that the automated systems might not process correctly. This human-in-the-loop approach helps to ensure the accuracy and reliability of the processed data, especially in cases where document content is complex or unstructured, or has hard-to-read text like handwriting or poor-quality images.
- Data validation and quality assurance: Human experts are crucial for data validation tasks, reviewing outputs to catch any inconsistencies or inaccuracies. This includes validating extracted information, verifying that data conforms to required formats, and making corrections where automated systems fall short. The combination of automated validation checks and human oversight significantly boosts the overall quality and trustworthiness of the processed data.
- Managed service advantage: Choosing an IDP solution that includes a managed service means you’re getting the benefits of the technology and gaining access to a dedicated team of professionals who manage and optimize the solution on your behalf. There’s no software to buy, implement, or maintain—eliminating the burden on your internal staff and allowing them to focus on other priorities. With a managed service, you benefit from continuous support, system maintenance, and improvements, ensuring the IDP solution runs smoothly and efficiently without any extra effort on your part.
- Training and improving algorithms: Humans are involved in the initial training of ML algorithms by providing labeled data and feedback. They help refine the models by correcting errors and improving the system’s learning process, which increases the accuracy of data extraction over time.
- Handling exceptions: While IDP systems can handle most standard document types, there are always exceptions or edge cases where the system may struggle. Humans are necessary to manage these exceptions, ensuring that all documents are processed correctly.
- Strategic oversight: Humans are also involved in overseeing the entire IDP solution implementation, from setting up the system to monitoring its performance. They ensure that the technology aligns with business goals and can intervene if any adjustments or strategic changes are needed.
Pro tip:
Seek out an IDP solution with far reaching HITL capabilities. Due to the speed and accuracy needed to process documents, a solution with an 24/7 on-demand global workforce is your best bet.
benefits of intelligent document processing
Intelligent Document Processing is a total game-changer for businesses. You might think, “Do I really need this?”
You do. Here’s why.
IDP software will boost efficiency and reduce stress
By automating document workflows, you can bid farewell to tedious manual data entry and say hello to more time for important tasks. You can have all your documents processed and sorted without lifting a finger.
IDP software cuts down on errors
We all know that humans make mistakes—especially when it comes to repetitive tasks like data entry. With Intelligent Document Processing, those errors become a thing of the past. IDP uses advanced AI and ML plus HITL to ensure accuracy, so you can trust that your data is spot-on.
IDP tools save money
Implementing IDP can lead to big cost savings. Think about all the money you spend on manual labor and correcting errors. With IDP you can cut those costs drastically. Plus, with more efficient processes, your team can focus on value-added activities that drive your business forward.
Embrace digital transformation
Staying ahead means embracing new technologies. Intelligent Document Processing is a key player in the digital transformation of document management. It modernizes your workflows and seamlessly integrates with other digital tools and systems of record, creating a cohesive and efficient system.
IDP solutions will help you scale
As your business grows, so does the volume of incoming documents. Manually processing all that data just isn’t feasible. IDP tools scale with your business, effortlessly handling increasing workloads. Whether you’re a small startup or a large enterprise, Intelligent Document Processing adapts to your needs, making it a smart investment for long-term growth.
Pro tip:
Look for an IDP service that can handle sudden volume spikes effortlessly while maintaining turnaround times and top performance.
For instance, see how a partnership with Noventi enabled them to scale their document processing capabilities without compromising on speed or accuracy. By leveraging ScaleHub’s IDP service, Noventi was able to manage unexpected surges in document volume efficiently, ensuring consistent, high-quality output and client satisfaction.
IDP services will enhance security
A quality IDP solution or service will go to the ends of the earth to make sure your sensitive information is secure. Automated processes reduce the risk of human error, and advanced security features ensure that your data is protected at every step. This peace of mind is invaluable, especially in industries that deal with uber-sensitive documents like medical records or insurance claims.
Pro tip:
Look for a partner who takes data privacy seriously by using hybrid deployments, snippeting, and/or a specialized workforce when necessary, to conform to regional data regulations or sensitive data risk adjudication.
Our solution allows you to keep the full document image within your own environment, sending only snippets into the cloud for processing. This approach ensures that sensitive data remains secure and under your control.
Snippeting is when document images and/or fields are broken down and separated into small bits of information called snippets. These completely anonymous data nuggets are deprived of any context that could jeopardize data privacy. And if, for some reason, sensitive data must be exposed, it can be sent to a specialized crowd—one with more specific skills and data compliance certifications to match the task.
Watch this video to learn more about snippeting:
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More Informationkey challenges faced when setting up an IDP service
Data security and compliance
IDP systems must manage sensitive data, such as that found in financial records or medical documents, which requires strict adherence to data protection laws like GDPR or HIPAA. Ensuring an IDP solution meets all compliance requirements while maintaining high levels of data security can be challenging, particularly in heavily regulated industries.
Integrating with existing systems
Integrating an IDP solution with legacy systems can be a royal pain. The complexity of ensuring smooth data flow between the IDP solution and other tools can lead to workflow disruptions if not managed carefully. Poor integration may result in data silos and reduce the overall efficiency of document processing.
Overlooking the pivotal role of humans
Businesses often overlook the crucial role of a human workforce in the IDP process. It’s important to acknowledge that while IDP technology is advancing, it still cannot fully replicate human cognitive abilities.
Completely shifting a process from human operation to IDP can produce mixed results, which is why it’s essential to implement these technologies with human-in-the-loop capabilities.
Pro tip:
Partner with an IDP provider with access to a 24/7 global on-demand workforce. By combining IDP with human expertise available around the clock, businesses can ensure that documents are processed efficiently and accurately, no matter the time zone or volume of work.
Data complexity and variety
Processing everything from structured forms to unstructured emails and scanned images can result in inconsistencies and errors in data extraction if an IDP solution is not properly configured. This complexity requires significant effort to ensure the solution can accurately process all types of documents.
Cost and resource allocation
Implementing an IDP solution involves substantial costs, including software, hardware, training, professional services, and ongoing maintenance. Allocating the necessary resources, both financial and human, can be challenging, particularly for small and medium-sized businesses that may struggle with the high initial investment.
Change management
People hate change. Shifting to an IDP system requires significant changes in workflows and employee roles. Resistance to change, coupled with inadequate training, can hinder the adoption of a new system. Effective change management strategies are essential to ensure that employees adapt smoothly and that the IDP system is fully utilized.
Scale issues
As a business grows, its document processing needs may expand, requiring its IDP solution to scale as well. Not all IDP solutions are designed for easy scalability, which can lead to performance bottlenecks and inefficiencies as document volumes increase. Ensuring that the chosen IDP solution can scale with the business is crucial to maintaining smooth operations.
Zero strategy
Many businesses start with a proof of concept (PoC), but without a solid business case, it’s challenging to demonstrate how IDP can be scaled.
This can lead to difficulties in justifying the investment to business leaders, ultimately resulting in unmet expectations. Without a well-defined strategy in your PoC, managing the vast number of documents your business handles—often in various formats—can become overwhelming.
This lack of clarity can lead to disappointing outcomes as the system struggles to meet demands.
things to consider when setting up an IDP solution or service
Understand your current processes
Once you’ve identified your process bottlenecks and selected Intelligent Document Processing (IDP) as a solution, the first step is to gain a complete understanding of your current processes. If you’re processing insurance forms, for example, start by identifying which invoices are still being handled manually. By doing this, you’ll gain a clear understanding of where inefficiencies lie, allowing you to present a compelling case to your finance team that highlights the labor savings an IDP solution can provide.
Gain buy-in by demonstrating quick wins
After securing internal buy-in to purchase and implement an IDP solution, the next step is to research and identify the minimum viable product (MVP) that IDP can deliver. This MVP is an example to your C-Suite, demonstrating the quick returns and efficiency gains that IDP can provide. Showcasing these early successes will help build momentum and support for broader implementation across the organization.
Explore the full scope of IDP solutions
A common mistake businesses make when working with IDP platforms is not fully exploring the range of solutions it can offer. Many organizations focus solely on the labor savings associated with automating invoice processing.
However, it’s crucial to consider other areas where IDP can add value. For example, IDP can streamline contract management by automating the extraction and organization of key terms and dates from vendor agreements. This ensures important deadlines are met, reducing the risk of missed renewals or compliance issues, and ultimately strengthening vendor relationships.
Focus on speedy response times and long-term value
Whether it’s paying a supplier on time, approving a loan for a new business, or making a patient’s health records available at a specialty clinic, time is critical when processing the documents that enable these actions. An IDP-fueled process ensures that documents are processed quickly and accurately, allowing payments to suppliers to be made promptly—or even faster. When suppliers are paid on time, they view your business as trustworthy and reliable, strengthening those relationships.
Best practices for Intelligent Document Processing
To optimize Intelligent Document Processing, focus on regularly updating your solution to handle new types of documents and data. Ensure that your team is well-trained to use the technology effectively, and consider starting with a small-scale implementation to test and refine the process.
Additionally, it’s important to avoid common pitfalls like neglecting data security, overlooking the need for regular maintenance (if an on-premises solution), or failing to integrate the solution with your existing tools and workflows.
case studies and examples
Healthcare service provider NOVENTI scales up billing processing with managed crowdsourcing service
Read how NOVENTI enlisted collective intelligence to relieve staff amidst extremely strict patient data protection regulations and significant day-to-day fluctuations in medical prescription volumes.
VRC processes 1 million handwritten delivery tickets in < 45 days
Community Brands saves money, slashes processing time, and boosts data security
questions to ask an IDP solutions provider
Listen for: Smart algorithms. A proven quality control system. A combination of AI and human intelligence. It’s all part of an equation that yields the highest-quality data outcomes.
Listen for: Service level agreements. Dividing and conquering processing volumes between AI and humans. A global, 24/7 workforce means they can guarantee turnaround times. Some in as little as an hour.
Listen for: A confident yes. Cloud-native. Fully automated platform that can divide document processing tasks among a global crowd that’s available 24/7. No job is too big.
Listen for: That’s easy. Unanticipated volume increases are seamlessly processed with no hit to performance. A proven technology that balances and scales workloads as needed.
Listen for: Help desk and issue resolution support (is it 24/7? Where is support based?); implementation support (does it include onboarding assistance? Integration and/or customization support?); documentation and training (are there established user guides? Do they provide a knowledge base? Any training programs?); customer success (will I have dedicated account support and how often?); performance monitoring and optimization; updates and maintenance; backup and disaster recovery.
Listen for: Structured, semi-structured, and unstructured documents and buzzwords like computer vision, NLP, and GenAI.
Listen for: Your uptime guarantees should be outlined in your Service Level Agreement (SLA), but generally, the larger IDP providers that cater to enterprise clients can guarantee high levels of uptime.
Regarding ongoing training, listen for: Periodic training sessions and/or webinars to keep users and IT staff informed about new features, updates, and best practices (tip: training sessions should be quick and easy to integrate into your team’s schedule).
Listen for: If a cloud-native IDP solution, your existing IT infrastructure should be sufficient as long as it meets the basic requirements for accessing cloud applications.
For an on-premises IDP solution, you’ll need dedicated servers to host and operate the system. The exact specifications will vary based on the number of documents you process and how complex your workflows are. You’ll also need sufficient storage, ideally high-speed, to ensure fast data retrieval and processing. A reliable network infrastructure is crucial, taking into account network speed, bandwidth, and security. The network must support smooth data exchange, and you’ll need a compatible operating system and, most likely, a database management system to handle data storage and organization efficiently.
If you have a managed service, you only need a reliable, high-speed internet connection.
If an on-premises IDP solution, the responsibilities are typically divided between the provider’s team and your internal IT staff.
If a cloud-native IDP solution is needed, the provider’s team should handle configurations.
If a managed service, all configurations are handled by the provider.
Listen for: A user experience that is highly intuitive, offering a clean, user-friendly interface that allows teams to get up and running quickly with minimal training. The system automates the majority of document processing tasks, so businesses don’t need large teams managing workflows. You’ll want a seamless design that ensures your team can focus on core business activities while intelligent automation handles the heavy lifting.
Listen for: Typical deployment time for an on-premises IDP tool ranges from approximately 8 to 20 weeks. For a cloud-native IDP tool, the typical deployment time is 6 to 12 weeks. For an IDP managed service, deployment can take as little as a few days to 2 weeks.
Are you ready to discover how ScaleHub can give your team precious time back, slash costs, and unlock massive scalability?
frequently asked questions
The best IDP solutions combine AI, ML, and OCR to handle structured and unstructured data. These solutions include ScaleHub, ABBYY FlexiCapture, and UiPath Document Understanding, which provide scalable automation, accuracy, and integration with existing workflows. ScaleHub offers 100% automation and >99% accuracy by combining a GenAI-powered IDP service fueled by a 24/7 global workforce.
IDP improves data accuracy by using AI and ML to automate data extraction, reducing human error, and employing HITL validation to ensure the precision of processed documents.
IDP cuts costs by automating manual data entry, reducing labor expenses, and accelerating document processing times, which leads to faster turnaround and fewer errors requiring costly corrections. IDP services can plug into existing workflows to alleviate inefficiencies and save money.
Top IDP companies include ABBYY, ScaleHub, UiPath, and Kofax, all of which offer advanced AI-driven solutions for efficient and scalable document processing across industries.
Generative AI applications in document processing enhance data extraction, improve accuracy by filling in missing information, and automate complex tasks like document categorization and summarization.
Unstructured data refers to information that doesn’t fit into predefined formats, such as emails, scanned images, or contracts, and requires advanced tools like AI and NLP to process and analyze.
Automated document processing uses technologies like AI, OCR, and machine learning to capture, extract, and process data from documents with minimal human intervention, improving speed and accuracy.
In healthcare, IDP automates the processing of medical records, insurance claims, and patient data, improving accuracy, reducing processing times, and ensuring compliance with regulations like HIPAA.
In insurance, IDP tools accelerates the handling of claims, policies, and underwriting by automating document classification, data extraction, and validation, leading to faster processing and reduced errors.
IDP solutions can integrate with ERP systems through APIs or connectors, ensuring smooth data flow and automation of document-related tasks without disrupting existing workflows or requiring major system overhauls.